The Myth of the Addicted Army: Vietnam and the Modern War on Drugs. By Jeremy Kuzmarov. (Amherst: University of Massachusetts Press, 2009. xiv, 303 pp. Cloth, $80.00, ISBN 978-1-55849-704-7. Paper, $26.95, ISBN 978-1-55849-705-4.)
Bibliographic record
Abstract
This book knits together historical threads from American foreign and domestic policies, the war on drugs, and medical debates over the nature of addiction and its treatment to demonstrate how intricately and completely drugs have become part of the history of the Vietnam War and the Cold War era. At the heart of this study is an investigation into the relationship between drugs and Americans and the degree to which a pervasive war on drugs has persistently molded public policies since the 1960s. Jeremy Kuzmarov's study is roughly divided into two sections. The first teases apart the mythology surrounding exaggerated claims of drug abuse by American soldiers in Vietnam who allegedly then brought that plague back to America. Readers receive a dove's rendering of the war and the antiwar movement as Kuzmarov examines how the media and political rhetoricians manipulated the drug problem to help justify, and at times legitimate, cruel interventions. The mythology, as represented in selective popular media, television, and film sources, reinforced an image of the all-American-boy-turned-junkie by virtue of exposure to addictive drugs, including marijuana, heroin, and hallucinogens. This mythology further indicates that widespread drug abuse produced inefficient soldiers and a weakening of morale, which was responsible for poor performances and even heinous crimes, including “fragging” and civilian massacres. According to the myth, drugs, not policies, lay at the heart of these disasters.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".